SXSW Panel – Time Traveling: Interfaces for Geotemporal Visualization

Summary:
Displaying geography alone is easy: interactive maps are more and more a part of our everyday lives. Displaying time alone is easy: we are all familiar with charts and animations that show the passage of time. It is increasingly common to display time and space together in a single visual interface as well, but this combination has raised a number of new questions. There are few conventions or standards for geotemporal visualization, and we are still discovering which approaches are most effective for which datasets. Focusing particularly on historical data, this panel will explore issues in the modeling and visualization of geotemporal information, presenting existing approaches and discussing new trends.

Trust and reputation – where does this problem arise in geotemporal visualization?

Honestly.com – one way to verify identity, in order to build online trust

Tao of Journalism seal – transparent accountable open

Netflix (?) – put an award out to anybody who could improve recommendation systems.

Ryan Shaw – Asst ProfessorUniversity of North Carolina at Chapel Hill

Visualizations are constrained by the data we have. If we want richer visualizations, we need richer data

Events, and not dates, are what have the most significance for visualizations over time

What should a data model for events look like?

Wikipedia thinks it’s a box – wikipeda block of text, and picture. Boring. We can do better

Better to think of events as a block, like a falling tetris block, and can fit in to the overall picture. But unlike a tetris block, events don’t have a natural state. Shapes of events change as stories change. We can understand this better if we make analogy with time and space.

Trendsmap.com is a real-time mapping of Twitter trends across the world.

The Neighborhood Project is creating a map of city neighborhoods based on the collective opinions of internet users. Addresses and neighborhood data are translated into latitude and longitude values, and then drawn on the map. The address and neighborhood data are collected from housing posts on craigslist, and from people filling out the form below. The coordinates are generated using the free geocoder.us. The map is from the TIGER/Line US Census data. Our first city is San Francisco, but we will add more soon. Or you can download the software and make your own.

Trendsmap.com is a real-time mapping of Twitter trends across the world.